BIG DATA AND ANALYTICS FOR BEGINNERS: Complete Beginner To Expert Guide On Handling Big Numbers, Huge Primary And Secondary Data, Statistics For Proper Decision Making

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Description of BIG DATA AND ANALYTICS FOR BEGINNERS: Complete Beginner To Expert Guide On Handling Big Numbers, Huge Primary And Secondary Data, Statistics For Proper Decision Making

START MAKING PROPER MANAGERIAL DECISIONS BY BREAKING DOWN BIG DATA

Big Data has become a new buzz word in the IT industry. Everyone is talking about it and repeatedly using it to impress others, even if they themselves don't really know what it means. It is often used out of context and more as a marketing gimmick. This book aims to explain what Big Data really is, how to use the information and knowledge, and how it will be useful in solving problems.

Physics and Mathematics calculations can give us the exact distance from the East Coast of the USA to the West Coast, accurate to about 1 yard. This is a phenomenal achievement and has been applied to various technologies in our daily life. But the challenge comes in when you have data which is not static, which is constantly changing and changing at a rate and in volumes which are humongous to determine in real time. The only way we can process this data is by using computers.

IBM data scientists break big data into four dimensions: volume, variety, velocity and veracity. But there are many more aspects of it and Big data can be described by the a lot of other characteristics.

While explaining this, Volume is the size of the data which determines the value and potential of the data under consideration and whether it can actually be considered as Big Data or not.

Variety means that the category to which the data belongs to is also a very essential fact that needs to be known by the data analysts. This helps the people, who are closely analyzing the data and are associated with it, to effectively use the data to their advantage and thus upholding the importance of the data.

Velocity refers to how fast the data is generated and processed to be useful. Variability of the data can also be a problem for the analysts. Veracity is the quality of the data being captured. Accurate analysis depends on the veracity of the source data.